The primary use of linear regression is to fit a line to 2 sets of data and determine how much they are related.
2 sets of stock prices
rainfall and crop output
study hours and grades
With respect to correlation, the general consensus is:
Correlation values of 0.8 or higher denote a strong correlation
Correlation values of 0.5 or higher up to 0.8 denote a weak correlation
Correlation values less than 0.5 denote a very weak correlation\f